Mapping the Predicted Loss of NYC Rent-Stabilization

library(tidyverse)
library(leaflet)
library(RColorBrewer)
library(sf)
library(htmltools)

# read data
df_pred_small <- read_csv("/Users/cpreeldumas/Documents/GitHub/MLC_SP23/clean_data/df_pred_small.csv") %>% 
  rename(BBL = bbl)

df_pred_big <- read_csv("/Users/cpreeldumas/Documents/GitHub/MLC_SP23/clean_data/df_pred_big.csv") %>% 
  rename(BBL = bbl)

pluto <- read_sf("/Users/cpreeldumas/Desktop/NYU/SPRING 2023/ML for Cities/Project/nyc_mappluto_23v1_shp/MapPLUTO.shp")

cdist <- read_sf("/Users/cpreeldumas/Desktop/NYU/SPRING 2023/ML for Cities/Project/nycd_23a/nycd.shp") %>% 
  rename(CD = BoroCD)

BBL level, Small Buildings

# prep data
df_small <- pluto %>% 
  select(BBL, CD, BCT2020, Borough) %>% 
  inner_join(df_pred_small %>% select(BBL, preds_small), by = "BBL") %>% 
  st_as_sf

pal_small <- colorBin(c("#BD0026", "#F03B20", "#FD8D3C", "#FECC5C", "#FFFFB2"), 
                      domain = df_small$preds_small, bin = 5)


leaflet() %>% 
  addProviderTiles(providers$CartoDB.Positron) %>% 
  addPolygons(data = df_small %>% st_transform(4326),
              stroke = ~pal_small(preds_small),
              color = ~pal_small(preds_small),
              weight = 5,
              fillOpacity = 0.7) %>% 
  addLegend("bottomright", pal = pal_small, values = df_small$preds_small, 
            opacity = 1, title = HTML('Change in Share of RS Units <br>
                                      Small Buildings')) 

---

CD level

# prep data
df_small_cd <- pluto %>% 
  st_drop_geometry() %>% 
  select(BBL, CD, BCT2020, Borough) %>% 
  inner_join(df_pred_small, by = "BBL") %>% 
  group_by(CD) %>% 
  summarise(mean_preds_small = round(mean(preds_small, na.rm = TRUE), digits = 3)) %>% 
  inner_join(cdist, by = "CD") %>% 
  st_as_sf

df_big_cd <- pluto %>% 
  st_drop_geometry() %>% 
  select(BBL, CD, BCT2020, Borough) %>% 
  inner_join(df_pred_big, by = "BBL") %>% 
  group_by(CD) %>% 
  summarise(mean_preds_big = round(mean(preds_big, na.rm = TRUE), digits = 3)) %>% 
  inner_join(cdist, by = "CD") %>% 
  st_as_sf

Small Buildings

pal_small <- colorBin(c("#BD0026", "#F03B20", "#FD8D3C", "#FECC5C", "#FFFFB2"), 
                      domain = df_small_cd$mean_preds_small, bin = 5)

leaflet() %>% 
  addProviderTiles(providers$CartoDB.Positron) %>% 
  addPolygons(group = "Small Buildings",
              data = df_small_cd %>%  st_transform(4326),
              fillColor = ~pal_small(mean_preds_small),
              weight = 1,
              color = "black", 
              fillOpacity = 0.7, 
              popup = paste0(
                "<b>CD: </b>",
                df_small_cd$CD,
                "<br>",
                "<b>Mean Change in Share of RS Units: </b>",
                df_small_cd$mean_preds_small
              )) %>% 
  addLegend("bottomright", pal = pal_small, values = df_small_cd$mean_preds_small, 
            opacity = 1, title = HTML(
            'CD-Level Mean Change in <br>
            Share of RS Units <br>
            Small Buildings')) 

Big Buildings

pal_big <- colorBin(c("#FD8D3C", "#FECC5C", "#FFFFB2"), 
                      domain = df_big_cd$mean_preds_big, bin = 3)

leaflet() %>% 
  addProviderTiles(providers$CartoDB.Positron) %>% 
    addPolygons(
              data = df_big_cd %>%  st_transform(4326),
              fillColor = ~pal_big(mean_preds_big),
              weight = 1,
              color = "black", 
              fillOpacity = 0.7, 
              popup = paste0(
                "<b>CD: </b>",
                df_big_cd$CD,
                "<br>",
                "<b>Mean Change in Share of RS Units: </b>",
                df_big_cd$mean_preds_big
              )) %>% 
  addLegend("bottomright", pal = pal_big, values = df_big_cd$mean_preds_big, 
            opacity = 1, title = HTML(
            'CD-Level Mean Change in <br>
            Share of RS Units <br>
            Big Buildings'))